code: def test_regression(
      regression_data,
      multi_target,
      continuous_cols,
      categorical_cols,
      continuous_feature_transform,
      normalize_continuous_features,
  ):
      (train, test, target) = regression_data
      if len(continuous_cols) + len(categorical_cols) == 0:
          assert True
      else:
          data_config = DataConfig(
              target=target + ["MedInc"] if multi_target else target,
              continuous_cols=continuous_cols,
              categorical_cols=categorical_cols,
              continuous_feature_transform=continuous_feature_transform,
              normalize_continuous_features=normalize_continuous_features,
          )
          model_config_params = {"task": "regression", "depth": 2}
          model_config = NodeConfig(**model_config_params)
          # model_config_params = dict(task="regression")
          # model_config = NodeConfig(**model_config_params)
  
          trainer_config = TrainerConfig(
              max_epochs=1, checkpoints=None, early_stopping=None
          )
          optimizer_config = OptimizerConfig()
  
          tabular_model = TabularModel(
              data_config=data_config,
              model_config=model_config,
              optimizer_config=optimizer_config,
              trainer_config=trainer_config,
          )
          tabular_model.fit(train=train)
  
          result = tabular_model.evaluate(test)
          if multi_target:
              assert result[0]["valid_loss"] < 30
          else:
              assert result[0]["valid_loss"] < 8
          pred_df = tabular_model.predict(test)
          assert pred_df.shape[0] == test.shape[0]
  
file_path: pytorch_tabular/examples/__only_for_dev__/to_test_node.py
imports: import numpy
  import pandas
  from pytorch_tabular.config import DataConfig, OptimizerConfig, TrainerConfig
  from pytorch_tabular.models.node import NodeConfig
  from pytorch_tabular.tabular_model import TabularModel
  from sklearn.datasets import fetch_california_housing, fetch_covtype
label_desc: Use image node_id 3 for calling a global function with example usage: test_regression(regression_data, multi_target, continuous_cols, categorical_cols, continuous_feature_transform, normalize_continuous_features) without return types